Efficient data reads from distributed storage systems

ABSTRACT

A method of distributing data in a distributed storage system includes receiving a file and dividing the received file into chunks. The chunks are data-chunks and non-data chunks. The method further includes grouping chunks into a group and determining a distribution of the chunks of the group among storage devices of the distributed storage system based on a maintenance hierarchy of the distributed storage system. The maintenance hierarchy includes hierarchical maintenance levels and maintenance domains. Each maintenance domain has an active state or an inactive state; and each storage device is associated with at least one maintenance domain. The method also includes distributing the chunks of the group to the storage devices based on the determined distribution. The chunks of the group are distributed across multiple maintenance domains to maintain an ability to reconstruct chunks of the group when a maintenance domain is in the inactive state.

CROSS REFERENCE TO RELATED APPLICATIONS

This U.S. patent application is a continuation of, and claims priorityunder 35 U.S.C. §120 from, U.S. patent application Ser. No. 15/079,095,filed on Mar. 24, 2016, which is a continuation of U.S. patentapplication Ser. No. 14/169,322, filed on Jan. 31, 2014. The disclosuresof these prior applications are considered part of the disclosure ofthis application and are hereby incorporated by reference in theirentireties.

TECHNICAL FIELD

This disclosure relates to efficient data reads from distributed storagesystems.

BACKGROUND

A distributed system generally includes many loosely coupled computers,each of which typically includes a computing resource (e.g., one or moreprocessors) and/or storage resources (e.g., memory, flash memory, and/ordisks). A distributed storage system overlays a storage abstraction(e.g., key/value store or file system) on the storage resources of adistributed system. In the distributed storage system, a server processrunning on one computer can export that computer's storage resources toclient processes running on other computers. Remote procedure calls(RPC) may transfer data from server processes to client processes.Alternatively, Remote Direct Memory Access (RDMA) primitives may be usedto transfer data from server hardware to client processes.

SUMMARY

One aspect of the disclosure provides a method of distributing data in adistributed storage system. The method includes receiving a file intonon-transitory memory and dividing the received file into chunks using acomputer processor in communication with the non-transitory memory. Themethod also includes grouping one or more of the data chunks and one ormore of the non-data chunks in a group. One or more chunks of the groupare capable of being reconstructed from other chunks of the group. Themethod further includes distributing chunks of the group to storagedevices of the distributed storage system based on a hierarchy of thedistributed storage system. The hierarchy includes maintenance domainshaving active and inactive states. Moreover, each storage device isassociated with a maintenance domain. The chunks of a group aredistributed across multiple maintenance domains to maintain the abilityto reconstruct chunks of the group when a maintenance domain is in aninactive state.

Implementations of the disclosure may include one or more of thefollowing features. In some implementations, the method further includesrestricting the number of chunks of a group distributed to storagedevices of any one maintenance domain.

In some implementations, the method includes determining a distributionof the chunks of a group among the storage devices by determining afirst random selection of storage devices that matches a number ofchunks of the group and determining if the selection of storage devicesis capable of maintaining accessibility of the group when one or moreunits are in an inactive state. In some examples, when the first randomselection of storage devices is incapable of maintaining accessibilityof the group when one or more maintenance domains are in an inactivestate, the method further includes determining a second random selectionof storage devices that match the number of chunks of the group ormodifying the first random selection of storage devices by adding orremoving one or more randomly selected storage devices. The method mayfurther include determining the first random selection of storagedevices using a simple sampling, a probability sampling, a stratifiedsampling, or a cluster sampling.

In some implementations, the method includes determining a distributionof the chunks of the group among the storage devices by selecting aconsecutive number of storage devices equal to a number of chunks of thegroup from an ordered circular list of the storage devices of thedistributed storage. When the selected storage devices are collectivelyincapable of maintaining the accessibility of the group when one or moremaintenance domains are in an inactive state, the method furtherincludes selecting another consecutive number of storage devices fromthe ordered circular list equal to the number of chunks of the group.The method may include determining the ordered circular list of storagedevices of the distributed storage system. Adjacent storage devices onthe ordered circular list are associated with different maintenancedomains. In some examples, a threshold number of consecutive storagedevices on the ordered circular list are each associated with differentmaintenance domains or are each in different geographical locations.

In some implementations, the method includes determining the maintenancehierarchy of maintenance domains (e.g., using the computer processor),where the maintenance hierarchy has maintenance levels and eachmaintenance level includes one or more maintenance domains. The methodalso includes mapping each maintenance domain to at least one storagedevice. In some examples, each maintenance domain includes storagedevices powered by a single power distribution unit or a single powerbus duct.

The method may include dividing the received file into stripes. Eachfile includes an error correcting code. The error correcting code is oneof a nested code or a layered code. The non-data chunks includecode-check chunks, word-check chunks, and code-check-word-check chunks.

Another aspect of the disclosure provides a system for distributing datain a distributed storage system. The system includes non-transitorymemory, a computer processor, and storage devices. The non-transitorymemory receives a file. The computer processor communicates with thenon-transitory memory and divides the received files into chunks. Thechunks are data-chunks and non-data chunks. The computer processorfurther groups one or more of the data chunks and one or more thenon-data chunks in a group. One or more chunks of the group are capableof being reconstructed from other chunks of the group. The storagedevices communicate with the computer processor and the non-transitorymemory. The computer processor stores the chunks of the group on thestorage devices based on a maintenance hierarchy of the distributedstorage system. The maintenance hierarchy includes maintenance domainshaving active and inactive states. Each storage device is associatedwith a maintenance domain. The computer processor distributes the chunksof a group across multiple maintenance domains to maintain accessibilityof the group when a maintenance domain is in an inactive state.

In some examples, the computer processor restricts a number of chunks ofthe group distributed to storage devices of any one maintenance domain.The computer processor may determine a distribution of the chunks of thegroup among the storage devices by determining a first random selectionof storage devices matching a number of chunks of the group and bydetermining if the selection of storage devices is capable ofmaintaining accessibility of the group when one or more maintenancedomains are in an inactive state. The computer processor may determine asecond random selection of storage devices matching the number of chunksof the group when the first random selection of storage devices isincapable of maintaining accessibility of the group when one or moremaintenance domains are in an inactive state.

In some implementations, the computer processor modifies the firstrandom selection of storage devices by adding and removing one or morerandomly selected storage devices when the first random selection ofstorage devices is incapable of maintaining accessibility of the filewhen one or more maintenance domains are in an inactive state. Thecomputer processor may determine the first random selection of storagedevices using a simple sampling, a probability sampling, a stratifiedsampling, or a cluster sampling.

In some examples, the computer processor determines a distribution ofthe chunks among the storage devices by selecting a consecutive numberof storage devices equal to a number of chunks of the group from anordered circular list of the storage devices of the distributed storagesystem. Moreover, the computer processor may select another consecutivenumber of storage devices from the ordered circular list equal to thenumber of chunks of the group, when the selected storage devices arecollectively incapable of maintaining the accessibility of the groupwhen one or more maintenance domains are in an inactive state.

In some implementations, the computer processor determines the orderedcircular list of storage devices of the distributed storage system,where adjacent storage devices on the ordered circular list areassociated with different maintenance domains. Additionally oralternatively, a threshold number of consecutive storage devices on theordered circular list may each be associated with different maintenancedomains. Additionally or alternatively, a threshold number ofconsecutive storage devices on the ordered circular list may each be indifferent geographical locations.

In some examples, the computer processor determines a maintenancehierarchy of maintenance domains and maps each maintenance domain to atleast one storage device. The maintenance hierarchy has maintenancelevels, with each maintenance level including one or more maintenancedomains. Each maintenance domain may include storage devices powered bya single power distribution unit or a single power bus duct.

In some implementations, the computer processor divides the receivedfile into stripes, with each file including an error correcting code.The error correcting code is one of a nested code or a layered code. Thenon-data chunks include code-check chunks, word-check chunks, andcode-check-word-check chunks.

The details of one or more implementations of the disclosure are setforth in the accompanying drawings and the description below. Otheraspects, features, and advantages will be apparent from the descriptionand drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1A is a schematic view of an exemplary distributed storage system.

FIG. 1B is a schematic view of an exemplary distributed storage systemhaving a cell of memory hosts managed by a curator.

FIG. 2 is a schematic view of an exemplary curator for a distributedstorage system.

FIG. 3A is a schematic view of an exemplary file split into stripes.

FIG. 3B is a schematic view of an exemplary file split into data chunksand code chunks.

FIG. 3C is a schematic view of an exemplary Reed-Solomon codingtechnique.

FIGS. 3D-3F are schematic views of exemplary layered coding techniques.

FIG. 3G is an exemplary arrangement of operations for storing data usinglayered coding techniques.

FIGS. 3H-3J are schematic views of exemplary nested coding techniques.

FIG. 3K is an exemplary arrangement of operations for storing data usingnested coding techniques.

FIGS. 4A-4C are schematic views of an exemplary maintenance hierarchy.

FIG. 5A is a flow chart of an exemplary arrangement of operations forrandomly selecting a group of storage resources.

FIG. 5B is a schematic view of an exemplary random selection of storagedevices.

FIG. 6A is a flow chart of an exemplary arrangement of operations forrandomly selecting a group of storage resources then randomly updatingstorage devices within the group.

FIG. 6B is a schematic view of an exemplary random selection of storagedevices.

FIG. 7A is a flow chart of an exemplary arrangement of operations forselecting a group of storage resources from a circular list.

FIG. 7B is a schematic view of an exemplary selection of storage devicesfrom an ordered list.

FIG. 8 is a schematic view of an exemplary arrangement of operations fordistributing data in a storage system.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

Storage systems include multiple layers of redundancy where data isreplicated and stored in multiple data centers. Data centers housecomputer systems and their associated components, such astelecommunications and storage systems 100 (FIGS. 1A and 1B). Datacenters usually include backup power supplies, redundant communicationsconnections, environmental controls (to maintain a constanttemperature), and security devices. Data centers may be large industrialscale operations that use a great amount of electricity (e.g., as muchas a small town). Data centers may be located in different geographicallocations (e.g., different cities, different countries, and differentcontinents). In some examples, the data centers, or a portion thereof,require maintenance (e.g., due to a power outage or disconnecting aportion of the storage system for replacing parts, or a system failure,or a combination thereof). The data stored in these data centers may beunavailable to users during the maintenance period resulting in theimpairment or halt of a user's operations. Therefore, it is desirable toprovide a distributed storage system 100 where a user is capable ofretrieving stored data or reconstructing unhealthy or lost data despitethe storage system 100 or portions thereof undergoing maintenance or asystem failure.

Referring to FIGS. 1A and 1B, in some implementations, a distributedstorage system 100 includes loosely coupled memory hosts 110, 110 a-n(e.g., computers or servers), each having a computing resource 112(e.g., one or more processors or central processing units (CPUs)) incommunication with storage resources 114 (e.g., memory, flash memory,dynamic random access memory (DRAM), phase change memory (PCM), and/ordisks) that may be used for caching data 312. A storage abstraction(e.g., key/value store or file system) overlain on the storage resources114 allows scalable use of the storage resources 114 by one or moreclients 120, 120 a-n. The clients 120 may communicate with the memoryhosts 110 through a network 130 (e.g., via RPC).

In some implementations, the distributed storage system 100 is“single-sided,” eliminating the need for any server jobs for respondingto remote procedure calls (RPC) from clients 120 to store or retrievedata 312 on their corresponding memory hosts 110 and may rely onspecialized hardware to process remote requests 122 instead.“Single-sided” refers to the method by which most of the requestprocessing on the memory hosts 110 may be done in hardware rather thanby software executed on CPUs 112 of the memory hosts 110. Rather thanhaving a processor 112 of a memory host 110 (e.g., a server) execute aserver process 118 that exports access of the corresponding storageresource 114 (e.g., non-transitory memory) to client processes 128executing on the clients 120, the clients 120 may directly access thestorage resource 114 through a network interface controller (NIC) 116 ofthe memory host 110. In other words, a client process 128 executing on aclient 120 may directly interface with one or more storage resources 114without requiring execution of a routine of any server processes 118executing on the computing resources 112. This single-sided distributedstorage architecture offers relatively high-throughput and low latency,since clients 120 can access the storage resources 114 withoutinterfacing with the computing resources 112 of the memory hosts 110.This has the effect of decoupling the requirements for storage 114 andCPU cycles that typical two-sided distributed storage systems 100 carry.The single-sided distributed storage system 100 can utilize remotestorage resources 114 regardless of whether there are spare CPU cycleson that memory host 110; furthermore, since single-sided operations donot contend for server CPU 112 resources, a single-sided system canserve cache requests 122 with very predictable, low latency, even whenmemory hosts 110 are running at high CPU utilization. Thus, thesingle-sided distributed storage system 100 allows higher utilization ofboth cluster storage 114 and CPU 112 resources than traditionaltwo-sided systems, while delivering predictable, low latency.

In some implementations, the distributed storage system 100 includes astorage logic portion 102, a data control portion 104, and a datastorage portion 106. The storage logic portion 102 may include atransaction application programming interface (API) 350 (e.g., asingle-sided transactional system client library) that is responsiblefor accessing the underlying data 312, for example, via RPC orsingle-sided operations. The data control portion 104 may manageallocation and access to storage resources 114 with tasks, such asallocating storage resources 114, registering storage resources 114 withthe corresponding network interface controller 116, setting upconnections between the client(s) 120 and the memory hosts 110, handlingerrors in case of machine failures, etc. The data storage portion 106may include the loosely coupled memory hosts 110, 110 a-n.

The distributed storage system 100 may store data 312 in dynamic randomaccess memory (DRAM) 114 and serve the data 312 from the remote hosts110 via remote direct memory access (RDMA)-capable network interfacecontrollers 116. A network interface controller 116 (also known as anetwork interface card, network adapter, or LAN adapter) may be acomputer hardware component that connects a computing resource 112 tothe network 130. Both the memory hosts 110 a-n and the client 120 mayeach have a network interface controller 116 for network communications.A host process 118 executing on the computing processor 112 of thememory host 110 registers a set of remote direct memory accessibleregions 115 a-n of the memory 114 with the network interface controller116. The host process 118 may register the remote direct memoryaccessible regions 115 a-n of the memory 114 with a permission ofread-only or read/write. The network interface controller 116 of thememory host 110 creates a client key 302 for each registered memoryregion 115 a-n.

The single-sided operations performed by the network interfacecontrollers 116 may be limited to simple reads, writes, andcompare-and-swap operations, none of which may be sophisticated enoughto act as a drop-in replacement for the software logic implemented by atraditional cache server job to carry out cache requests and managecache policies. The transaction API 350 translates commands, such aslook-up or insert data commands, into sequences of primitive networkinterface controller operations. The transaction API 350 interfaces withthe data control and data storage portions 104, 106 of the distributedstorage system 100.

The distributed storage system 100 may include a co-located softwareprocess to register memory 114 for remote access with the networkinterface controllers 116 and set up connections with client processes128. Once the connections are set up, client processes 128 can accessthe registered memory 114 via engines in the hardware of the networkinterface controllers 116 without any involvement from software on thelocal CPUs 112 of the corresponding memory hosts 110.

Referring to FIG. 1B, in some implementations, the distributed storagesystem 100 includes multiple cells 200, each cell 200 including memoryhosts 110 and a curator 210 in communication with the memory hosts 110.The curator 210 (e.g., process) may execute on a computing processor 202(e.g., server having a non-transitory memory 204) connected to thenetwork 130 and manage the data storage (e.g., manage a file systemstored on the memory hosts 110), control data placements, and/orinitiate data recovery. Moreover, the curator 210 may track an existenceand storage location of data 312 on the memory hosts 110. Redundantcurators 210 are possible. In some implementations, the curator(s) 210track the striping of data 312 across multiple memory hosts 110 and theexistence and/or location of multiple copies of a given stripe forredundancy and/or performance. In computer data storage, data stripingis the technique of segmenting logically sequential data 312, such as afile 310 (FIG. 2) into stripes, in a way that accesses of sequentialsegments are made to different physical memory hosts 110 (e.g., cells200 and/or memory hosts 110). Striping is useful when a processingdevice requests access to data 312 more quickly than a memory host 110can provide access. By performing segment accesses on multiple devices,multiple segments can be accessed concurrently. This provides more dataaccess throughput, which avoids causing the processor to idly wait fordata accesses. In some implementations (discussed in more detail below),each stripe may be further divided into groups G (e.g., includingchunks), where accesses of sequential groups G are made to differentphysical memory hosts 110. Grouping of segments within a stripe may alsobe useful when a processing device requests access to data 312 morequickly than a memory host 110 can provide access. By providing segmentaccess of a group G on multiple devices, multiple segments of a group Gcan be accessed concurrently. This also provides more data accessthroughput, which avoids causing the processor to idly wait for dataaccesses, thus improving the performance of the system 100.

In some implementations, the transaction API 350 interfaces between aclient 120 (e.g., with the client process 128) and the curator 210. Insome examples, the client 120 communicates with the curator 210 throughone or more remote procedure calls (RPC). In response to a clientrequest 122, the transaction API 350 may find the storage location ofcertain data 312 on memory host(s) 110 and obtain a key 302 that allowsaccess to the data 312. The transaction API 350 communicates directlywith the appropriate memory hosts 110 (via the network interfacecontrollers 116) to read or write the data 312 (e.g., using remotedirect memory access). In the case that a memory host 110 isnon-operational, or the data 312 was moved to a different memory host110, the client request 122 fails, prompting the client 120 to re-querythe curator 210.

Referring to FIG. 2, in some implementations, the curator 210 stores andmanages file system metadata 212. The metadata 212 may include a filemap 214 that maps files 310 _(1-n) to file descriptors 300 _(1-n). Thecurator 210 may examine and modify the representation of its persistentmetadata 212. The curator 210 may use three different access patternsfor the metadata 212: read-only, file transactions, and stripetransactions. For example, the metadata 212 can specify which parts of afile 310 are stored at which data centers, where redundant copies ofdata 312 are stored, which data chunks 330 nD and code chunks 330 nCform codewords, and the like.

Referring to FIGS. 3A-3K, data 312 may be one or more files 310. Thecurator 210 may divide each file 310 into a collection of stripes 320a-n, with each stripe 320 a-n being encoded independently from theremaining stripes 320 a-n. Each stripe 320 may be encoded and stored ondifferent memory hosts 110. As shown in FIG. 3A, each stripe 320 isdivided into data-chunks 330 nD and non-data chunks 330 nC based on anencoding level 313, e.g., Reed-Solomon Codes (FIG. 3B), layered codes(FIGS. 3C-3G), or nested codes (FIGS. 3H-3K), or other hierarchicalcodes. The non-data chunks 330 nC may be code chunks 330 nC (e.g., forReed Solomon codes). In other examples, the non-data chunks 330 nC maybe code-check chunks 330 nCC, word-check chunks 330 nWC, andcode-check-word-check chunks 330 nCCWC (for layered or nested coding). Adata chunk 330 nD is a specified amount of data 312. In someimplementations, a data chunk 330 nD is a contiguous portion of data 312from a file 310. In other implementations, a data chunk 330 nD is one ormore non-contiguous portions of data 312 from a file 310. For example, adata chunk 330 nD can be 256 bytes or other units of data 312.

A damaged chunk 330 (e.g., data chunk 330 nD or non-data chunk 330 nC)is a chunk 330 containing one or more errors. Typically, a damaged chunk330 is identified using an error detecting code 313. For example, adamaged chunk 330 can be completely erased (e.g., if the chunk 330 wasstored in a hard drive destroyed in a hurricane), or a damaged chunk 330can have a single bit flipped. A healthy chunk 330 is a chunk 330 thatis not damaged. A damaged chunk 330 can be damaged intentionally, forexample, where a particular memory host 110 is shut down formaintenance. A damaged chunk may be a missing or unavailable chunk. Inthat case, damaged chunks 330 can be identified by identifying chunks330 that are stored at memory hosts 110 that are being shut down.

The non-data chunks 330 nC of a file 310 include the error-correctingcode chunk 313. The error-correcting code chunks 313 include a chunk 330of data 312 based on one or more data-chunks 330 nD. In someimplementations, each code chunk 330 nC is the same specified size(e.g., 256 bytes) as the data chunks 330 nD. The code chunks 330 nC aregenerated using an error-correcting code 313, e.g., a Maximal DistanceSeparable (MDS) code. Examples of MDS codes include Reed-Solomon codes.Various techniques can be used to generate the code chunks 330 nC. Forexample, an error-correcting code 313 can be used that can reconstruct ddata chunks 330 nD from any set of unique, healthy chunks 330 (eitherdata chunks 330 nD or code chunks 330 nC).

A codeword is a set of data chunks 330 nD and code chunks 330 nC basedon those data chunks 330 nD. If an MDS code is used to generate acodeword containing d data chunks 330 nD and c code chunks 330 nC, thenall of the chunks 330 (data or code) can be reconstructed as long as anyd healthy chunks 330 (data or code) are available from the codeword.

FIG. 3B shows a Reed-Solomon encoding as the error-correcting codechunks 313. Each stripe 320 is divided into chunks 330 stored onmultiple storage resources 114. The chunks 330 may be data chunks 330nD_(k) or code chunks 330 nC_(m), which together form a single codeword. The data chunks 330 nD_(k) include the actual data 312; while thecode chunks 330 nC_(m) are for parity to determine if the file 310 isintact. The Reed-Solomon encoding allows for the loss of up to the totalnumber of code chunks 330 nC_(m) where the stripe 312 may still bereconstructed from the data chunk 330 nD_(k). Therefore, each stripe 320a-n of a file 310 consists of multiple data chunks 330 nD_(k) and codechunks 330 nC_(m) that the curator 210 places on multiple storageresources 114, where the collection of data chunks 330 nD_(k) and codechunks 330 nC_(m) forms a single code word. In general, the curator 210may place each stripe 320 a-n on storage resources 114 independently ofhow the other stripes 320 a-n in the file 310 are placed on storageresources 114. The Reed-Solomon Encoding 313 adds redundant data 312, orparity data 312 to a file 310, so that the file 310 can later berecovered by a receiver even when a number of errors (up to thecapability of the code being used) were introduced. Reed-SolomonEncoding 313 is used to maintain data integrity in memory hosts 110, toreconstruct data 312 for performance (latency), or to more quickly drainmachines.

Referring to FIGS. 3C-3I, in layered coding (FIGS. 3C-3G) and nestedcoding (FIGS. 3H-3K) techniques, an encoded data block 314 includes adata block 316 (having data chunks 330 nD) and error-correcting codechunks 313 (i.e., non-data chunks 330 nC) that is being stored is viewedas forming a two dimensional R×C array. There are X code chunks 330 nCfor each column C (called “code-check chunks 330 nCC”) that can be usedto reconstruct X or fewer damaged chunks 330 per column C. There are Ycode chunks 330 nC (called “word-check chunks 330 nWC”) for the entire2-D array. When there are more than X damaged chunks 330 in one or morecolumns C, the word-check chunks 330 nWC are used in addition to otherhealthy chunks 330 to reconstruct damaged chunks 330. Although someexamples described in this specification illustrate encoded data blocks314 (i.e., data blocks 316 and code chunks 330 nC (i.e., non-data chunks330 nC)) as forming a two dimensional array, it is possible for codingtechniques to create encoded data blocks 314 configured differently. Forinstance, different columns can have different numbers of code-checkchunk 330 nCC, and columns that contain word-check chunks 330 nWC canhave different numbers of rows R than columns C that contain data chunks330 nD and code-check chunks 330 nC.

The codes 330 nC can be used to store data 312 across memory hosts 110by allocating each column C of data chunks 330 nD to a data center. Eachchunk 330 within the column C can be allocated to a memory host 110within a data center. Then, if X or fewer chunks 330 are lost at a datacenter, the chunks 330 can be reconstructed using only intra-data centercommunication (e.g., so no other data centers have to provide data 312in performing reconstruction). If more than X chunks 330 are lost in oneor more data centers, then the Y word-check chunks 330 nWC are used toattempt reconstruction. Thus, inter-data center communication (which maybe more expensive, e.g., slower than intra-data center communication) isonly needed when more than X chunks 330 are damaged within a single datacenter.

The codes can also be used within a single data center. Instead ofallocating different columns C to different data centers, the encodingsystem 102 stores all of the columns C at a single data center. The datachunks 330 nD and code chunks 330 nC can be stored at distinct memoryhosts 110 within that data center. This is useful, for example, wherereading data 312 from memory hosts 110 during reconstruction isexpensive (e.g., time consuming), so that the encoding system 102 canread fewer chunks 330 during reconstruction than would be needed usingconventional coding techniques. Small numbers of damaged chunks 330 canbe reconstructed by reading small numbers of other chunks 330(code-check chunks 330 nCC and other data chunks 330 nD in a column C),and large numbers of damaged chunks 330 can be reconstructed using theword-check chunks 330 nWC when needed. In some examples, the curator 210groups data chunks 330 nD and certain non-data chunks 330 nC in a groupG in a manner that allows the system 100 to reconstruct missing chunks330 from other chunks 330 of the group G. The group G may include one ormore columns C or portions thereof.

Referring to FIGS. 3C-3G, in some implementations, a layered codingtechnique shows data chunks 330 nD and code chunks 330 nC formingcodewords. An error-correcting code 313 is in systematic form ifresulting codewords can be partitioned into two sets of chunks 330, oneset including the data chunks 330 nD and one set including the codechunks 330 nC. A code in systematic form is Maximal Distance Separable(MDS) if it has N code chunks 330 nC and it can correct any N damagedchunks 330. A layered code is created from two MDS codes, e.g.,Reed-Solomon codes or parity codes, in systematic form. One code is usedto create the code-check chunks 330 nCC and the other code is used tocreate the word-check chunks 330 nWC.

Referring to the example shown in FIGS. 3D-3F, a data block 316 includesdata chunks 330 nD labeled D0-D41 that are encoded with a layered code.In FIG. 3D, a first columns of data chunks 330 nD is shown, D0-D5. Twocode-check chunks 330 nCC are shown for the columns, C0 and C1. C0 andC1 are based on D0-D5. Thus, D0-D5 and C0-C1 form a codeword. In FIG.3E, an encoded data block 314 having the data block 314 (D0-D41) and sixcode chunks C0-05 is shown. C0-05 are based on D0-D41. Thus, D0-D41 andC0-05 form a codeword.

FIG. 3F illustrates the resulting encoded data block 314 that includesthe data block 314 (D0-D41) and additional code chunks 330 nC(code-check chunks 330 nCC and word-check chunks 330 nWC). The i-thcode-check chunk in column j is denoted Ci,j. So C0,0 and C1,0 are bothcode-check chunks 330 nCC for D0-D5.

Together, D0-D5 and C0,0 and C1,0 form a codeword. The word-check chunksC0-05 are shown in the last column to the right. Together, D0-D41 andC0-05 form a codeword. C1,7 and C1,7 can be generated based on C0-05, sothat C0,7 and C1,7 and C0-05 form a codeword.

In the example shown in FIG. 3F, the word-check chunks 330 nWC fill awhole column C. However, layered codes can be created with an arbitrarynumber of full Columns C of word-check chunks 330 nWC plus an optionalpartial column of word-check chunks 330 nWC. If the data chunks 330 nDand the word-check chunks 330 nWC do not fill an integral number ofcolumns C, empty zero-valued chunks 330 can be added to the 2D array.Those chunks 330 do not have to actually be stored and they would neverbe in error.

In general, a layered code with X code-check chunks 330 nCC_(k) percolumn C and N word-check chunks 330 nWC can reconstruct up to X damagedchunks 330 per column while performing only intra-column Ccommunication. If after reconstructing those damaged chunks 330, N orfewer damaged chunks 330 remain in the 2D array (within the data plusword-check chunks 330 nWC portion of the 2D array), the damaged chunks330 can be reconstructed using the word-check chunks 330 nWC and thecode-check chunks 330 nCC. This is true because N or fewer damagedchunks 330 in the data chunks 330 nD plus the word-check chunks 330 nWCcan be reconstructed using only the word-check chunks 330 nWC. Then, ifany code-check chunks 330 nCC_(k) are damaged, they can be reconstructedfrom the data chunks 330 nD of their respective column C.

Referring to FIG. 3G, in some implementations, the curator 210distributes data 312 using a layered code. The curator 210 receives adata block 316 that includes data chunks 330 nD (step 362). For example,the data block 316 can be from a file 310 that is being stored. The datablock 316 can include m_(d)*n_(d) data chunks 330 nC, m_(d) is a numberof data rows and n_(d) is a number of data columns, and m_(d) and n_(d)are greater than or equal to one. The encoded block 314 includes m*nchunks 330 that include m_(d)*n_(d), where m is the total number of rowsR of data chunks 330 nD and non-data chunks 330 nC, and n is the numberof columns C of data chunks 330 nD and non-data chunks 330 nC; m and nare greater than or equal to one. The curator 210 generates one or morecolumns C of word-check chunks 330 nWC using a first error-correctingcode 313 in systematic form and the data chunks 330 nD (step 364). Thecolumns C of word-check chunks 330 nWC can have different numbers ofword-check chunks 330 nWC in the column C. The data chunks 330 nD andthe word-check chunks 330 nWC, taken together, form a codeword.

For each column C of one or more columns C of the data chunks 330 nD,the curator 210 generates one or more code-check chunks 330 nCC for thecolumn C using a second error-correcting code 313 in systematic form andthe data chunks 330 nD of the column C (step 366). The first and seconderror-correcting codes 313 can be distinct. The columns C can havedifferent numbers of code-check chunks 330 nCC. The system 100 can alsogenerate code-check chunks 330 nCC for the column C of word-check chunks330 nWC. The system 100 stores the data chunks 330 nD, code-check chunks330 nCC, and word-check chunks 330 nWC (step 368). In someimplementations, the system 100 allocates each columns C and/or thecode-check chunks 330 nCC within a column C to a distinct group ofmemory host 110. In other implementations, the system 100 stores thedata chunks 330 nD and the code chunks 330 nC at a same group of memoryhost 110, e.g., a single data center. The system 100 may group datachunks 330 nD and certain code-check chunks 330 nCC, and word-checkchunks 330 nWC in groups G where an unhealthy chunk 330 can be restoredfrom one or more other chunks 330 of the group G. Therefore, the system100 stores chunks 330 of a group G at different memory hosts 110.

When the system allocates a column C of chunks 330 to a group of memoryhosts 110, the code-check chunks 330 nCC can be generated at differentlocations. For example, the code-check chunks 330 nCC can be generatedby a central encoding system (e.g., the server 202 of FIG. 1B) thatperforms the allocation or by the group of memory hosts 110 afterreceiving a column C of data chunks 330 nD. At each group of memoryhosts 110, each of the allocated data chunks 330 nD, code-check chunks330 nCC, and word-check chunks 330 nWC can be stored at a distinctmemory host 110.

When the system 100 identifies a damaged data chunk 330 nD at a firstgroup of memory hosts 110, the system 100 attempts to reconstruct thedamaged chunk 330 without communication with other groups of memoryhosts 110 (using the code-check chunks 330 nCC) of the group G of chunks330. In some cases, the system 100 reconstructs as many other damageddata chunks 330 nD from the group G of chunks 330 at the first group ofmemory hosts 110 as is possible using the code-check chunks 330 nCC andany healthy data chunks 330 nD allocated to the first group of memoryhosts 110 from the group G of chunks 330. If the system 100 determinesthat the damaged chunk 330 cannot be reconstructed without communicatingwith other groups of memory hosts 110 that have other groups G of chunks330, the system identifies (e.g., by requesting and receiving) healthychunks 330 from other groups of memory hosts 110 that have other groupsG of chunks 330 so that at least m*n healthy chunks 330 are available,where the healthy chunks 330 are data chunks 330 nD, word-check chunks330 nWC, or both, and reconstructs the damaged data chunk 330 nD usingthe healthy chunks 330.

Referring to FIGS. 3H-3J, in some implementations, a nested codingtechnique shows data chunks 330 nD and code chunks 330 nC that form acodeword. As shown, the nested coding technique is a two dimensional(2D) nested coding technique, but a three dimensional (3D) nested codingtechnique may also be applied.

Nested coding techniques differ from layered coding techniques bycreating a different relationship between the code-check chunks 330 nCCand the word-check chunks 330 nWC. A 2D nested code is created from anarbitrary linear MDS code in systematic form. Word-check chunks 330 nWCthat are based on a data block 316 are partitioned into two groups, thefirst group including X code chunks 330 nC and the second groupincluding N code chunks 330 nC. The encoded data block 316 is viewed asforming an array of columns C, and X code chunks 330 nC in the firstgroup are used to create X column chunks 330 per column by “splitting”them into separate components per column (“split” code-check chunks 330nCC). The N code chunks 330 nC in the second group form word-checkchunks 330 nWC.

For example, FIG. 3H shows a data block 314 (D0-D41) and code chunks(C0-C7) 330 nC that are based on the data block 316 (D0-D41). The datachunks (D0-D41) 330 nD and the code chunks (C0-C7) 330 nC form acodeword. The code chunks 330 nC are partitioned into a first group thatincludes C0-C1 and a second group that includes C2-C7. C0-CI are splitto form split code-check chunks 330 nCC. C2-C7 are used as word-checkchunks 330 nWC.

FIG. 3I shows a resulting encoded block 314 that includes the data block316 (D0-D41) and additional code chunks 330 nC (split code-check chunks330 nCC and word-check chunks 330 nWC). To generate a split code-checkchunk 330 nCC corresponding to C0 for column j (denoted C0,j), C0 isgenerated as though all the data chunks 330 nD not in column j have thevalue zero. That is, C0,j has the value that would result fromperforming the operations to generate C0 using the full data block 316but instead using only the column j, with all of the other columnszeroed out. For example, if a generator matrix would be used to generateC0 for the data block 314, then the generator matrix can be modified togenerate C0,j so that it has the value that would result from using theoriginal generator matrix and applying that original generator matrix tothe data block 316 with data chunks 330 nD in columns C other thancolumn j zeroed out.

The split code-check chunks 330 nCC for C1,j for each column C aregenerated similarly, but using C1 instead of C0. As a result, C0 is alinear combination of C0,0-C0,6 and C1 is a linear Combination ofC1,0-C1,6. That is,C0=Σ_(j=0) ⁶C0,j; and  (1)C1=Σ_(j=0) ⁶C1,j.  (2)

The chunks 330 denoted as “?” in FIG. 3I can be generated in variousways, e.g., as described further below with reference to FIG. 3J.

In the example of FIGS. 3H and 3I, the resulting encoded data block 314includes 42 data chunks 330 nD and 8 code chunks 330 nC. Referring tothe original code used to create the encoded block, the code chunks 330nC belong to one of two groups as described above, X=2 of which are inthe first group and N=6 of which are in the second group. Whenever thereare two or fewer (X or fewer) damaged chunks 330 within one of the firstseven columns, the damaged chunks 330 can be corrected using the healthychunks 330 of the columns C and the split code-check chunks 330 nCC forthe column C. To see this, let j denote the column C including the twoor fewer damaged chunks 330 and consider the codeword obtained byzeroing-out all the data chunks 330 nD from columns C other than j. Inthat codeword, C0=C0,j and C1=C1,j. As a result, the two or fewerdamaged chunks 330 in other columns as containing all-zero data chunks330 nD, and by viewing the word-check chunks 330 nWC as being damaged.

In the example shown in FIG. 3F, the word-check chunks 330 nWC fullyfill an entire column C (the column to the right). 2D nested codes 313 bcan be created with an arbitrary number of columns C of word-checkchunks 330 nWC. The columns C of word-check chunks 330 nWC can have thesame number of rows R as the columns of data chunks 330 nD or differentnumbers of rows R, and the columns C of word-check chunks 330 nWC canhave different numbers of rows R from each other. Columns C ofword-check chunks 330 nWC can, but do not have to, have code-checkchunks 330 nCC, i.e., code-check-word-check chunks 330 nCCWC. Increasingthe number of word-check chunks 330 nWC improves the reliability of thestored data 312 but uses more storage at memory hosts 110. In general,for nested codes columns C include either data chunks 330 nD orword-check chunks 330 nWC and not both.

In general, a 2D nested code with X split code-check chunks 330 nCC percolumn C and N word-check chunks 330 nWC can be used to reconstruct Xdamaged chunks 330 per column C (in those columns that include datachunks 330 nD) while performing only intra-columns communication (whichis typically, e.g., intra-data center communication). In reconstructingmultiple damaged chunks 330 within the encoded block 314, those damagedchunks 330 are typically reconstructed first because intra-columncommunication is less expensive than inter-column communication, butother damaged chunks 330 may remain. If, after reconstructing damagedchunks 330 within columns, (N+X) or fewer other chunks 330 are stilldamaged (because they were not able to be reconstructed usingintra-column communication), those other damaged chunks 330 can bereconstructed using the word-check chunks 330 nWC and the splitcode-check chunks 330 nCC. The word-check chunks 330 nWC in the firstgroup (C0 and C1 in FIG. 4B) can be determined from the split code-checkchunks 330 nCC, e.g., using the formula Ci=Σ_(j=0) ⁶C i, j, even thoughthose word-check chunks 330 nWC are not explicitly stored.

To see this, let Z denote the number of word-check chunks 330 nWC thatare damaged and let Y denote the number of word-check chunks 330 nWC inthe first group that cannot be reconstructed from their correspondingsplit code-check chunks 330 nCC according to the formula Ci=Σ_(j=0)⁶C0,j to split code-check chunks 330 nCC being damaged. Using thatformula, X-Y word-check chunks 330 nWC from the first group can bedetermined, resulting in a codeword (e.g., the one shown in FIG. 3H)with Y damaged word-check chunks 330 nWC in the first group and Zdamaged word-check chunks 330 nWC in the second group. Because there areat most N+X total damaged chunks 330, there are at most N+X−Y−Z damageddata chunks 330 nD. Thus, it is possible to use the resulting codewordto reconstruct all of the damaged chunks 330, as it includes at mostN+X−Y−Z+Y+Z=N+X damaged chunks 330.

Referring to FIG. 3J, in some implementations, a resulting encoded block314 includes code-check chunks 330 nCC for the word-check chunks 330 nWC(i.e., code-check-word-check chunks 330 nCCWC). Compared to the encodedblock of FIG. 3I, the encoded block 314 of FIG. 3J includes thecode-check chunks C0,7 and C1,7 330 nCC in place of the locations markedwith “?” in FIG. 3I. This is one way to provide for reconstructingdamaged word-check chunks 330 nWC without relying on inter-columncommunication. The code-check chunks C0,7 and C1,7 330 nCC can begenerated in various ways. For example, those code-check chunks 330 nCCcan be generated based on C2-C7 in the same manner that C0,0 and C1,0are generated based on D0-D5. The resulting encoded block 314 of FIG. 3J(using the example nested code) can be used to reconstruct up to eightdamaged chunks 330 after performing intra-column reconstruction, whereasthe resulting encoded block of FIG. 3E (using the example layered code)can be used to reconstruct up to six damaged chunks 330 after performingintra-column reconstruction. Code-check chunks 330 nC can be added forany number of columns that include word-check chunks 330 nWC.

Referring to FIG. 3K, in some implementations, the curator 210distributes data 312 using a nested code 313 b. The system 100 receivesa data block 316 (step 372). The data block 316 can include m_(d)*n_(d)data chunks 330 nC, m_(d) is a number of data rows and n_(d) is a numberof data columns, and m_(d) and n_(d) are greater than or equal to one.The encoded block 314 includes m*n chunks 330 that include m_(d)*n_(d),where m is the total number of rows R of data chunks 330 nD and non-datachunks 330 nC, and n is the number of columns C of data chunks 330 nDand non-data chunks 330 nC; m and n are greater than or equal to one.The system 100 generates one or more columns C of word-check chunks 330nWC using a first linear error-correcting code 313 in systematic formand the data chunks 330 nD (step 374). The word-check chunks 330 nWC andthe data chunks 330 nD of the same row R form a codeword. For each of marow of data chunks 330 nC, the system 100 generates one or more splitcode-check chunks 330 nCC for the Column C (step 376). The splitcode-check chunks 330 nCC are generated so that a linear combination ofn split code-check chunks 330 nCC from different columns C forms a firstword-check chunk 330 nWC of a first codeword including the data chunks330 nD and the m word-check chunks 330 nWC. The first word-check chunk330 nWC (and any other word-check chunks 330 nWC resulting from a linearcombination of split code-check chunks 330 nCC from different columns C)forms a codeword with the data chunks 330 nD and the word-check chunks330 nWC generated in step 374. For example, the split code-check chunks330 nCC for each columns C can be generated using a splittingerror-correcting code 313 and the ma data chunks 330 nD or theword-check chunks 330 nWC, wherein the splitting error-correcting code313 includes a splitting generator matrix that codes the same as agenerator matrix for the first linear error-correcting code 313 appliedto the data chunks 330 nD with the data chunks 330 nD zeroed-out forcolumns C other than the column C.

The system 100 stores the column C of data chunks 330 nD and the splitcode-check chunks 330 nCC and the word-check chunks 330 nWC (step 378).In some implementations, the system 100 stores all the chunks 330 at asingle group of memory hosts 110. In some other implementations, thesystem 100 allocates each column C to a distinct group of memory hosts110. In some implementations, the system 100 groups chunks 330 capableof being reconstructed from other chunks 330 within the group G, andallocates the chunks 330 of the group G to distinct groups of memoryhosts 110.

When the system 100 identifies one or more damaged chunks 330, thesystem 100 can reconstruct the damaged chunks 330 using the splitcode-check chunks 330 nCC and the word-check chunks 330 nWC. Typically,the system 100 attempts to reconstruct damaged chunks 330 using thesplit code-check chunks 330 nCC and other data chunks 330 nd in the samecolumn C. If, after reconstructing damaged chunks 330 using only thesplit code-check chunks 330 nCC, some damaged chunks 330 remain, thesystem 100 uses the word-check chunks 330 nWC for reconstruction,including the word-check chunks 330 nWC that can be determined bydetermining a linear combination of the split code-check chunks 330 nCC.In addition, if after reconstructing damaged chunks 330 using only splitcode-check chunks 330 nCC of chunks 330 of a group G, some damagedchunks 330 remain, the system 100 uses chunks 330 from other groups G ofchunks 330 to reconstruct the damaged chunks 330.

Referring back to FIG. 2, in some implementations, file descriptors 300_(1-n) stored by the curator 210 contain metadata 212, such as the filemap 214, which maps the stripes 320 a-n to data chunks 320 nd _(k) andnon-data chunks 320 nc _(m), as appropriate, stored on the memory hosts110. To open a file 310, a client 120 sends a request 122 to the curator210, which returns a file descriptor 300. The client 120 uses the filedescriptor 300 to translate file chunk offsets to remote memorylocations 115 a-n. The file descriptor 300 may include a client key 302(e.g., a 32-bit key) that is unique to a chunk 330 on a memory host 110and is used to RDMA-read that chunk 330. After the client 120 loads thefile descriptor 300, the client 120 may access the data 312 of a file310 via RDMA or another data retrieval method.

The curator 210 may maintain status information for all memory hosts 110that are part of the cell 200. The status information may includecapacity, free space, load on the memory host 110, latency of the memoryhost 110 from a client's point of view, and a current state. The curator210 may obtain this information by querying the memory hosts 110 in thecell 200 directly and/or by querying a client 120 to gather latencystatistics from a client's point of view. In some examples, the curator210 uses the memory host status information to make rebalancing,draining, recovery decisions, and allocation decisions.

The curator(s) 210 may allocate chunks 330 in order to handle clientrequests 122 for more storage space in a file 310 and for rebalancingand recovery. The curator 210 may maintain a load map 216 of memory hostload and liveliness. In some implementations, the curator 210 allocatesa chunk 330 by generating a list of candidate memory hosts 110 and sendsan allocate chunk request 122 to each of the candidate memory hosts 110.If the memory host 110 is overloaded or has no available space, thememory host 110 can deny the request 122. In this case, the curator 210selects a different memory host 110. Each curator 210 may continuouslyscan its designated portion of the file namespace, examining all themetadata 212 every minute or so. The curator 210 may use the file scanto check the integrity of the metadata 212, determine work that needs tobe performed, and/or to generate statistics. The file scan may operateconcurrently with other operations of the curator 210. The scan itselfmay not modify the metadata 212, but schedules work to be done by othercomponents of the system 100 and computes statistics.

In some implementations, the processor 202 may group one or more of thedata chunks 330 nD and one or more of the non-data chunks 330 nC in agroup G. The one or more chunks 330 of the group G are capable of beingreconstructed from other chunks 330 of the group G. Therefore, whenreconstructing chunks 330 of a group G, the curator 210 reads chunks 330of the group G to reconstruct damaged chunks 330 within the group G.This allows more efficient reconstruction of missing chunks 330, and thenumber of chunks 330 being read is reduced. Specifically, reducing thenumber of chunk reads can decrease the cost of the read, since fewerreads to hardware devices (e.g., memory hosts 114) are performed, andreduce the latency of the reconstruction since slow devices are lesslikely to be accessed.

Referring to FIGS. 4A-4C, the curator 210 may determine a maintenancehierarchy 400 of the distributed storage system 100 to identify thelevels (e.g., levels 1-5) at which maintenance may occur withoutaffecting a user's access to stored data 312. Maintenance may includepower maintenance, cooling system maintenance (FIG. 4C), networkingmaintenance, updating or replacing parts, or other maintenance or poweroutage affecting the distributed storage system 100.

The maintenance hierarchy 400 identifies levels (e.g., levels 1-5) ofmaintenance domains 402, where each maintenance domain 402 may be in anactive state or an inactive state. Each memory host 110 of thedistributed storage system 100 is associated with one or moremaintenance domain 402. Moreover, the processor 202 maps the associationof the memory hosts 110 with the maintenance domains 402 and theircomponents 410, 420, 430, 440, 114. FIG. 4A shows a strict hierarchy 400a where each component 410, 420, 430, 440, 114, depends on one othercomponent 410, 420, 430, 440, 114, while FIG. 4B shows a non-stricthierarchy 400 b where one component 410, 420, 430, 440, 114 has morethan one input feed. In some examples, the processor 202 stores themaintenance hierarchy 400 on the non-transitory memory 204 of theprocessor 202. For example, the storage resource 114 a is mapped to arack 440 a, which is mapped to a bus duct 430 a, which in turn is mappedto a power module distribution center 420 a, which in turn is mapped toa power plant 410 a. The processor 202 determines, based on the mappingsof the components 410, 420, 430, 440, 114, what memory hosts 110 areinactive when a component 410, 420, 430, 440, 114 is undergoingmaintenance. Once the system 100 maps the maintenance domains 402 to thestorage resources 114, the system 100 determines a highest level (e.g.,levels 1-5) at which maintenance can be performed while maintaining dataavailability.

A maintenance domain 402 includes a component 410, 420, 430, 440, 114undergoing maintenance and any components depending from that component410, 420, 430, 440, 114. Therefore, when one component 410, 420, 430,440, 114 is undergoing maintenance that component 410, 420, 430, 440,114 is inactive and any component 410, 420, 430, 440, 114 in themaintenance domain 402 of the component 410, 420, 430, 440, 114 is alsoinactive. As shown in FIG. 4A, level 1 components may include thestorage resources 114 a-n; level 2 components may include racks 440 a-n;level 3 components may include bus ducts 430 a-n; level 4 components mayinclude power module distribution centers 420 a-420 n; and level 5components may be the power plants 410 providing power to levels 1 to 4components. Other component distribution may also be available. When amemory host 110 a is undergoing maintenance, a level 1 maintenancedomain 402 a includes the memory host 110 and that storage device 114 isinactive. When a rack 440 a is undergoing maintenance, a level 2maintenance domain 402 b that includes the rack 440 a and memory hosts110 depending from the rack 440 a are in an inactive state. When a busduct 430 a is undergoing maintenance, a level 3 maintenance domain 402 cthat includes the bus duct 430 a and any components in levels 1 and 2that depend from the bus duct 430 a are in an inactive state. When apower module distribution center 420 a is undergoing maintenance, alevel 4 maintenance domain 402 d that includes the power moduledistribution center 420 a and any components in levels 1 to 3 dependingfrom the power module distribution center 420 a are in an inactivestate. Finally, when the power plant 410 is undergoing maintenance, alevel 5 maintenance domain 402 e including any power module distributioncenters 420, bus ducts 430, racks 440, and memory hosts 110 depending onthe power plant 410 are inactive, and therefore a user cannot accessdata 312 located within the level 1 maintenance domain 402 a.

In some examples, as shown in FIG. 4B, a non-strict hierarchy 400 bcomponent 410, 420, 430, 440, 114 has dual feeds, i.e., the component410, 420, 430, 440, 114 depends on two or more other components 410,420, 430, 440, 114. For example, a bus duct 430 n may have a feed fromtwo power modules 420; and/or a rack 440 may have a dual feed from twobus ducts 430. As shown, a first maintenance domain 402 c may includetwo racks 440 a and 440 n, where the second rack 440 n includes twofeeds from two bus ducts 430 a, 430 n. Therefore, the second rack 440 nis part of two maintenance domains 402 ca and 402 cb. Therefore, thehigher levels of the maintenance hierarchy 400 are maintained withoutcausing the loss of the lower levels of the maintenance hierarchy 400.This causes a redundancy in the system 100, which allows for dataaccessibility. In particular, the power module distribution center 420may be maintained without losing any of the bus ducts 430 depending fromit. In some examples, the racks 440 include a dual-powered rack 440 thatallows the maintenance of the bus duct 430 without losing power to thedual-powered racks 440 depending from it. In some examples, maintenancedomains 402 that are maintained without causing outages are ignored whendistributing chunks 330 to allow for maintenance; however, the ignoredmaintenance domains 402 may be included when distributing the chunks 330since an unplanned outage may still cause the loss of chunks 330.

In some examples, as shown in FIG. 4C, the maintenance hierarchy 400 isa cooling hierarchy 400 c (or a combination of a power hierarchy 400 a,400 b) and a cooling hierarchy 400 c. The cooling hierarchy 400 c maps acooling device 442 to the racks 440 that it is cooling. As shown, acooling device 442 may cool one or more racks 440. The processor 202stores the association of the memory hosts 110 with the coolingmaintenance domains 402 f. In some implementations, the processor 202considers all possible combinations of maintenance that might occurwithin the storage system 100 to determine a hierarchy 400 or acombination of hierarchies 400 a, 400 b, 400 c.

Therefore, when a component 410, 420, 430, 440, 114 in the storagesystem 100 is being maintained that component 410, 420, 430, 440, 114and any components 410, 420, 430, 440, 114 that are mapped to ordepending from that component 410, 420, 430, 440, 114 are in an inactivestate. A component 410, 420, 430, 440, 114 in an inactive state isinaccessible by a user, while a component 410, 420, 430, 440, 114 in anactive state is accessible by a user allowing a user to access data 312stored on that component 410, 420, 430, 440, 114 or on a memory host 110mapped to that component 410, 420, 430, 440, 114. As previouslymentioned, during the inactive state, a user is incapable of accessingthe memory hosts 110 associated with the maintenance domains 402undergoing maintenance; and therefore, the user is incapable ofaccessing the files 310 (i.e., chunks 330, which include stripe replicas330 n _(k), data chunks 330 nD_(k), and code chunks 330 nC_(m)).

In some implementations, the processor 202 restricts a number of chunks330 within a group G that are distributed to memory hosts 110 of any onemaintenance domain 402, e.g., based on the mapping of the components410, 420, 430, 440, 114. Therefore, if a level 1 maintenance domain 402is inactive, the processor 202 maintains accessibility (i.e., theunhealthy chunks 330 can be reconstructed) to the group G although somechunks 330 may be inaccessible. In some examples, for each group G ofchunks 330, the processor 202 determines a maximum number of chunks 330that are placed within any memory host 110 within a single maintenancedomain 402, so that if a maintenance domain 402 associated with thememory host 110 storing chunks 330 for a file 310 is undergoingmaintenance, the processor 202 may still retrieve the chunks 330 withinthe group G. The maximum number of chunks 330 ensures that the processor202 is capable of reconstructing the number of chunks 330 of the group Galthough some chunks 330 may be unavailable. In some examples, themaximum number of chunks 330 of a group G is set to a lower threshold toaccommodate for any system failures, while still being capable ofreconstructing the group G of chunks 330. When the processor 202 placeschunks 330 on the memory hosts 110, the processor 202 ensures thatwithin a group G of chunks 330 of a stripe 320, no more than the maximumnumber of chunks 330 are inactive when a single maintenance domain 402undergoes maintenance.

Referring to FIGS. 5A-7B, in some implementations, the processor 202determines a distribution of the chunks 330 of a group G among thememory hosts 110. In some examples, the processor 202 makes a firstrandom selection 150 of memory hosts 110 from an available pool ofstorage devices 140 to store the chunks 330 of a group G. The processor202 selects a number of memory hosts 110 (e.g., selected memory host110S) equal to the number of chunks 330 in the group G. Next, theprocessor 202 determines if the selection 150 of selected memory hosts110S is capable of maintaining accessibility of the group G (i.e., thechunks 330 of the group G are available) when one or more (or athreshold number of) maintenance domains 402 are in an inactive state.The random selection 150 has the goal of allowing reconstruction of thegroup G if maintenance occurs on one of the maintenance components 410,420, 430, 440, 114.

Referring to FIGS. 5A and 5B, in some examples, when the processor 202determines that the first random selection 150 a of selected memoryhosts 110S is incapable of maintaining accessibility of the group G whenone or more (or a threshold number of) maintenance domains 402 are in aninactive state, the processor 202 determines a second random selection150 b of selected memory hosts 110S that matches the number of chunks330 of the group G. Then, the processor 202 determines if the secondrandom selection 150 b of selected memory hosts 110S is capable ofmaintaining accessibility of the group G when one or more (or athreshold number of) maintenance domains 402 are in an inactive state.If the processor 202 determines that the second random selection 150 bis incapable of maintaining accessibility of the group G when one ormore (or a threshold number of) maintenance domains 402 are in aninactive state, the processor 202 continues to make random selections150 n of selected memory hosts 110S until the processor 202 identifies arandom selection 150 n of selected memory hosts 110S that is capable ofmaintaining accessibility of the group G.

Referring to FIGS. 6A and 6B, in some implementations, when theprocessor 202 determines that the first random 150 a selection ofselected memory hosts 110S is incapable of maintaining accessibility ofthe group G when one or more (or a threshold number of) maintenancedomains 402 are in an inactive state, the processor 202 modifies thefirst random selection 150 a of selected memory hosts 110S by adding oneor more randomly selected memory hosts 110S and removing a correspondingnumber of different memory hosts 110S. The processor 202 then determinesif the updated first random selection 150 a is capable of maintainingaccessibility of the group G when one or more (or a threshold number of)maintenance domains 402 are in an inactive state. If the processor 202determines that updated first random selection 150 a is incapable ofmaintaining accessibility of the group G when one or more (or athreshold number of) maintenance domains 402 are in an inactive state,the processor 202 updates the selection 150 a of selected memory hosts110S by adding and removing one or more randomly selected memory host110S. The processor 202 continues to update the random selection 150 aof memory hosts 110 until the processor 202 determines that the selectedmemory hosts 110S are capable of maintaining accessibility of the groupG of chunks 330 during maintenance of the distributed storage system100. Once the processor 202 makes that determination, the processor 202moves to the next stripe 320 (or file 310) to determine a distributionof the next stripe 320. In some implementations, the processor 202determines the random selection 150 of selected memory hosts 110S byusing a probability sampling, a simple sampling, a stratified sampling,a cluster sampling, or a combination therefrom.

Referring to FIGS. 7A and 7B, in some implementations, the processor 202determines a number of chunks 330 in a group G of chunks 330. Theprocessor 202 then selects a selected list 162 having a consecutivenumber of memory hosts 110 a-n equal to a number of chunks 330 of thefile 310 from an ordered circular list 160 of memory hosts 110 of thedistributed storage system 100, the ordered circular list 160 beginningat a first memory host 110 a. The list 160 may be stored on thenon-transitory memory 204 of the processor 202. The processor 202 thendetermines if the selected memory hosts 110 a-n from the selected list162 are collectively incapable of maintaining accessibility of the groupG of chunks 330 when one or more (or a threshold number of) maintenancedomains 402 are in an inactive state. If the processor 202 determinesthat the selected memory hosts 110 a-n are collectively incapable ofmaintaining the accessibility of the group G of chunks 330 when one ormore (or a threshold number of) maintenance domains 402 are in aninactive state, the processor 202 selects another selected list 162having a consecutive number of memory hosts 110 a-n from the orderedcircular list 160 equal to the number of chunks 330 of the stripe 320 orfile 310. In some examples, the processor 202 moves to a second memoryhost 110(n+1) after the first memory host 110 n in the ordered circularlist 160 when the processor 202 determines that memory hosts 110 a-n ofthe selected list 162 are collectively incapable of maintaining theaccessibility of the group G of chunks 330. In other examples, theprocessor 202 moves a predetermined number of positions down the orderedcircular list 160. In some implementations, the processor 202 determinesthe ordered circular list 160 of memory hosts 110 of the storage system100 where adjacent memory hosts 110 or a threshold number of consecutivememory hosts 110 on the ordered circular list 160 are associated withdifferent maintenance domains 402. Additionally or alternatively, theprocessor 202 determines the ordered circular list 160 of memory hosts110 of the storage system 100 where adjacent memory hosts 110 or athreshold number of consecutive memory hosts 110 on the ordered circularlist 160 is each in different geographical locations. In some examples,the memory hosts 110 on the ordered circular list 160 are arranged sothat different maintenance domains 402 cause the dispersion of data 312sequentially along the ordered list 160. For example, as shown in FIG.4A, the list 160 may not contain sequentially memory hosts 110 dependentfrom the same bust duct 430 a. Instead, two sequential memory hosts 110on the list 160 are from different maintenance domains 402 to make surethat data accessibility is maintained.

Referring to FIG. 8, in some implementations, a method 800 ofdistributing data 312 in a distributed storage system 100 includesreceiving 802 a file 310 into non-transitory memory 204 and dividing 804the received file 310 into chunks 330 using a computer processor 202 incommunication with the non-transitory memory 204. The method 800 alsoincludes grouping 806 one or more of the data chunks 330 and one or moreof the non-data chunks 330 in a group G. One or more chunks 330 of thegroup G are capable of being reconstructed from other chunks 330 of thegroup G. The method 800 further includes distributing 808 chunks 330 ofthe group G to storage devices 114 of the distributed storage system 100based on a hierarchy of the distributed storage system 100. Thehierarchy includes maintenance domains 402 having active and inactivestates. Moreover, each storage device 114 is associated with amaintenance domain 402. The chunks 330 of a group G are distributedacross multiple maintenance domains 402 to maintain the ability toreconstruct chunks 330 of the group G when a maintenance domain 402 isin an inactive state.

In some implementations, the method 800 further includes restricting thenumber of chunks 330 of a group G distributed to storage devices 114 ofany one maintenance domain 402. The method 800 further includesdetermining a distribution of the chunks 330 of a group G among thestorage devices 114 by determining a first random selection 150 a ofstorage devices 114 that matches a number of chunks 330 of the group Gand determining if the selection of storage devices 114 is capable ofmaintaining accessibility of the group G when one or more units 402 arein an inactive state. In some examples, when the first random selection150 a of storage devices 114 is incapable of maintaining accessibilityof the group G when one or more maintenance domains 402 are in aninactive state, the method 800 further includes determining a secondrandom selection 150 b of storage devices 114 that match the number ofchunks 330 of the group G or modifying the first random selection 150 aof storage devices 114 by adding or removing one or more randomlyselected storage devices 114. The method 800 may further includedetermining the first random selection 150 a of storage devices 114using a simple sampling, a probability sampling, a stratified sampling,or a cluster sampling.

In some implementations, the method 800 further includes determining adistribution of the chunks 330 of the group G among the storage devices114 by selecting a consecutive number of storage devices 114 equal to anumber of chunks 330 of the group G from an ordered circular list 160 ofthe storage devices 114 of the distributed storage. When the selectedstorage devices 114 are collectively incapable of maintaining theaccessibility of the group G when one or more maintenance domains 402are in an inactive state, the method 800 further includes selectinganother consecutive number of storage devices 114 from the orderedcircular list 160 equal to the number of chunks 330 of the group G.Additionally or alternatively, the method 800 further includesdetermining the ordered circular list 160 of storage devices 114 of thedistributed storage system 100. Adjacent storage devices 114 on theordered circular list 160 are associated with different maintenancedomains 402. In some examples, a threshold number of consecutive storagedevices 114 on the ordered circular list 160 are each associated withdifferent maintenance domains 402 or are each in different geographicallocations.

In some implementations, the method 800 further includes determining themaintenance hierarchy 400 of maintenance domains 402 (e.g., using thecomputer processor 202), where the maintenance hierarchy 400 hasmaintenance levels and each maintenance level includes one or moremaintenance domains 402. The method 800 also includes mapping eachmaintenance domain 402 to at least one storage device 114. In someexamples, each maintenance domain 402 includes storage devices 114powered by a single power distribution unit 420 or a single power busduct 430.

The method 800 may further include dividing the received file 310 intostripes 320. Each file 310 includes an error correcting code 313. Theerror correcting code 313 is one of a Reed-Solomon code, a nested codeor a layered code. The non-data chunks 330 include code-check chunks 330nCC, word-check chunks 330 nCC, and code-check-word-check chunks 330nCCWC.

Various implementations of the systems and techniques described here canbe realized in digital electronic circuitry, integrated circuitry,specially designed ASICs (application specific integrated circuits),computer hardware, firmware, software, and/or combinations thereof.These various implementations can include implementation in one or morecomputer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable medium” and“computer-readable medium” refer to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including a machine-readablemedium that receives machine instructions as a machine-readable signal.The term “machine-readable signal” refers to any signal used to providemachine instructions and/or data to a programmable processor.

Implementations of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Moreover,subject matter described in this specification can be implemented as oneor more computer program products, i.e., one or more modules of computerprogram instructions encoded on a computer readable medium for executionby, or to control the operation of, data processing apparatus. Thecomputer readable medium can be a machine-readable storage device, amachine-readable storage substrate, a memory device, a composition ofmatter affecting a machine-readable propagated signal, or a combinationof one or more of them. The terms “data processing apparatus”,“computing device” and “computing processor” encompass all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them. A propagated signal is an artificially generated signal, e.g.,a machine-generated electrical, optical, or electromagnetic signal thatis generated to encode information for transmission to suitable receiverapparatus.

A computer program (also known as an application, program, software,software application, script, or code) can be written in any form ofprogramming language, including compiled or interpreted languages, andit can be deployed in any form, including as a stand-alone program or asa module, component, subroutine, or other unit suitable for use in acomputing environment. A computer program does not necessarilycorrespond to a file in a file system. A program can be stored in aportion of a file that holds other programs or data (e.g., one or morescripts stored in a markup language document), in a single filededicated to the program in question, or in multiple coordinated files(e.g., files that store one or more modules, sub programs, or portionsof code). A computer program can be deployed to be executed on onecomputer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationnetwork.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

To provide for interaction with a user, one or more aspects of thedisclosure can be implemented on a computer having a display device,e.g., a CRT (cathode ray tube), LCD (liquid crystal display) monitor, ortouch screen for displaying information to the user and optionally akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

One or more aspects of the disclosure can be implemented in a computingsystem that includes a backend component, e.g., as a data server, orthat includes a middleware component, e.g., an application server, orthat includes a frontend component, e.g., a client computer having agraphical user interface or a Web browser through which a user caninteract with an implementation of the subject matter described in thisspecification, or any combination of one or more such backend,middleware, or frontend components. The components of the system can beinterconnected by any form or medium of digital data communication,e.g., a communication network. Examples of communication networksinclude a local area network (“LAN”) and a wide area network (“WAN”), aninter-network (e.g., the Internet), and peer-to-peer networks (e.g., adhoc peer-to-peer networks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someimplementations, a server transmits data (e.g., an HTML page) to aclient device (e.g., for purposes of displaying data to and receivinguser input from a user interacting with the client device). Datagenerated at the client device (e.g., a result of the user interaction)can be received from the client device at the server.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the disclosure or of what maybe claimed, but rather as descriptions of features specific toparticular implementations of the disclosure. Certain features that aredescribed in this specification in the context of separateimplementations can also be implemented in combination in a singleimplementation. Conversely, various features that are described in thecontext of a single implementation can also be implemented in multipleimplementations separately or in any suitable sub-combination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multi-tasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made without departingfrom the spirit and scope of the disclosure. Accordingly, otherimplementations are within the scope of the following claims. Forexample, the actions recited in the claims can be performed in adifferent order and still achieve desirable results.

What is claimed is:
 1. A method of distributing data in a distributedstorage system, the method comprising: receiving, at data processinghardware, a file; dividing, by the data processing hardware, thereceived file into chunks, the chunks being data-chunks and non-datachunks; grouping, by the data processing hardware, chunks into a group;determining, by the data processing hardware, a distribution of thechunks of the group among storage devices of the distributed storagesystem based on a maintenance hierarchy of the distributed storagesystem, the maintenance hierarchy comprising hierarchical maintenancelevels and maintenance domains, each maintenance domain having an activestate or an inactive state, each storage device associated with at leastone maintenance domain; and distributing, by the data processinghardware, the chunks of the group to the storage devices based on thedetermined distribution, the chunks of the group being distributedacross multiple maintenance domains to maintain an ability toreconstruct chunks of the group when a maintenance domain is in theinactive state.
 2. The method of claim 1, wherein the group comprisesone or more of the data chunks and one or more of the non-data chunks,and wherein one or more of the data chunks or one or more of thenon-data chunks of the group are capable of being reconstructed fromother chunks of the group.
 3. The method of claim 1, wherein eachmaintenance domain spans one or more adjacent hierarchical maintenancelevels.
 4. The method of claim 1, wherein the hierarchical maintenancelevels comprise: a storage device level; a rack level, the storagedevice level depending from the rack level; a bus duct level, the racklevel depending from the bus duct level; and a power distribution centerlevel, the bus duct level depending from the power distribution centerlevel, wherein each maintenance domain spans at least the storage devicelevel.
 5. The method of claim 1, further comprising restricting, by thedata processing hardware, a number of chunks of a group distributed tostorage devices of any one maintenance domain.
 6. The method of claim 1,wherein the distribution comprises a random selection of storage devicesmatching a number of the chunks of the group capable of maintainingaccessibility of the group when one or more maintenance domains are inthe inactive state.
 7. The method of claim 6, wherein when the randomselection of the storage devices is incapable of maintainingaccessibility of the group when one or more maintenance domains are inthe inactive state, modifying, by the data processing hardware, therandom selection of the storage devices by adding and/or removing one ormore randomly selected storage devices.
 8. The method of claim 6,further comprising determining, by the data processing hardware, thefirst random selection of storage devices using a simple sampling, aprobability sampling, a stratified sampling, or a cluster sampling. 9.The method of claim 1, wherein determining the distribution of thechunks of the group among the storage devices comprises selecting aconsecutive number of storage devices equal to a number of chunks of thegroup from an ordered circular list of the storage devices of thedistributed storage system.
 10. The method of claim 9, furthercomprising, when the selected storage devices are collectively incapableof maintaining the accessibility of the group when one or moremaintenance domains are in an inactive state, selecting, by the dataprocessing hardware, another consecutive number of storage devices fromthe ordered circular list equal to the number of chunks of the group.11. The method of claim 9, further comprising determining, by the dataprocessing hardware, the ordered circular list of storage devices of thedistributed storage system, adjacent storage devices on the orderedcircular list associated with different maintenance domains.
 12. Themethod of claim 11, wherein a threshold number of consecutive storagedevices on the ordered circular list are each at least one of:associated with different maintenance domains; or in differentgeographical locations.
 13. A system for distributing data in adistributed storage system, the system comprising: storage devices; anda computer processor in communication with the storage devices, thecomputer processor configured to perform operations comprising:receiving a file; dividing the received file into chunks, the chunksbeing data-chunks and non-data chunks; grouping the chunks into a group;determining a distribution of the chunks of the group among storagedevices of the distributed storage system based on a maintenancehierarchy of the distributed storage system, the maintenance hierarchycomprising hierarchical maintenance levels and maintenance domains, eachmaintenance domain having an active state or an inactive state, eachstorage device associated with at least one maintenance domain; anddistributing the chunks of the group to the storage devices based on thedetermined distribution, the chunks of the group being distributedacross multiple maintenance domains to maintain an ability toreconstruct chunks of the group when a maintenance domain is in theinactive state.
 14. The system of claim 13, wherein the group comprisesone or more of the data chunks and one or more of the non-data chunks,and wherein one or more of the data chunks or one or more of thenon-data chunks of the group are capable of being reconstructed fromother chunks of the group.
 15. The system of claim 13, wherein eachmaintenance domain spans one or more adjacent hierarchical maintenancelevels.
 16. The system of claim 13, wherein the hierarchical maintenancelevels comprise: a storage device level; a rack level, the storagedevice level depending from the rack level; a bus duct level, the racklevel depending from the bus duct level; and a power distribution centerlevel, the bus duct level depending from the power distribution centerlevel, wherein each maintenance domain spans at least the storage devicelevel.
 17. The system of claim 13, wherein the operations furthercomprise restricting a number of chunks of a group distributed tostorage devices of any one maintenance domain.
 18. The system of claim13, wherein the distribution comprises a random selection of storagedevices matching a number of the chunks of the group capable ofmaintaining accessibility of the group when one or more maintenancedomains are in the inactive state.
 19. The system of claim 18, whereinwhen the random selection of the storage devices is incapable ofmaintaining accessibility of the group when one or more maintenancedomains are in the inactive state, the operations further comprisemodifying the random selection of the storage devices by adding and/orremoving one or more randomly selected storage devices.
 20. The systemof claim 18, wherein the operations further comprise determining thefirst random selection of storage devices using a simple sampling, aprobability sampling, a stratified sampling, or a cluster sampling. 21.The system of claim 13, wherein determining the distribution of thechunks of the group among the storage devices comprises selecting aconsecutive number of storage devices equal to a number of chunks of thegroup from an ordered circular list of the storage devices of thedistributed storage system.
 22. The system of claim 21, wherein theoperations further comprise, when the selected storage devices arecollectively incapable of maintaining the accessibility of the groupwhen one or more maintenance domains are in an inactive state, selectinganother consecutive number of storage devices from the ordered circularlist equal to the number of chunks of the group.
 23. The system of claim21, wherein the operations further comprise determining the orderedcircular list of storage devices of the distributed storage system,adjacent storage devices on the ordered circular list associated withdifferent maintenance domains.
 24. The system of claim 23, wherein athreshold number of consecutive storage devices on the ordered circularlist are each at least one of: associated with different maintenancedomains; or in different geographical locations.